Background: techniques of image analysis have been used extensively to minimize interobserver variation of immunohistochemical scoring, yet; image acquisition procedures are often demanding, expensive and laborious. This study aims to assess the validity of image analysis to predict human observer’s score with a simplified image acquisition technique. Materials and methods: formalin fixed- paraffin embedded tissue sections for ameloblastomas and basal cell carcinomas were immunohistochemically stained with monoclonal antibodies to MMP-2 and MMP-9. The extent of antibody positivity was quantified using Imagej® based application on low power photomicrographs obtained with a conventional camera. Results of the software were employed

HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

In this paper, an efficient image segmentation scheme is proposed of boundary based & geometric region features as an alternative way of utilizing statistical base only. The test results vary according to partitioning control parameters values and image details or characteristics, with preserving the segmented image edges.

The hero traditionally has such admirable traits as courage, fortitude,
chivalry and patriotism. In the literary works, the hero is the leading
character and the pivot around which all the characters and the events
revolve. The characteristics of the hero usually reflect the cultural values
of his time. Because, in each age, Man's attitudes towards himself and the
world change, different images of the hero emerge.
In Greek Mythology, the hero is frequently favoured by the gods;
therefore, he is himself semi-divine. The Greek hero is of princely birth
and is endowed with good physique, exceptional strength, skill in
athletics and battle, energy and eloquence, like Odysseus who is the hero
of the Odyssey, long

<p>In this paper, a simple color image compression system has been proposed using image signal decomposition. Where, the RGB image color band is converted to the less correlated YUV color model and the pixel value (magnitude) in each band is decomposed into 2-values; most and least significant. According to the importance of the most significant value (MSV) that influenced by any simply modification happened, an adaptive lossless image compression system is proposed using bit plane (BP) slicing, delta pulse code modulation (Delta PCM), adaptive quadtree (QT) partitioning followed by an adaptive shift encoder. On the other hand, a lossy compression system is introduced to handle the least significant value (LSV), it is based on

The study focuses on assessment of the quality of some image enhancement methods which were implemented on renal X-ray images. The enhancement methods included Imadjust, Histogram Equalization (HE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The images qualities were calculated to compare input images with output images from these three enhancement techniques. An eight renal x-ray images are collected to perform these methods. Generally, the x-ray images are lack of contrast and low in radiation dosage. This lack of image quality can be amended by enhancement process. Three quality image factors were done to assess the resulted images involved (Naturalness Image Quality Evaluator (NIQE), Perception based Image Qual

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le